Accurate Classification of Chronic Migraine via Brain Magnetic Resonance Imaging

被引:102
|
作者
Schwedt, Todd J. [1 ]
Chong, Catherine D. [1 ]
Wu, Teresa [2 ]
Gaw, Nathan [2 ]
Fu, Yinlin [2 ]
Li, Jing [2 ]
机构
[1] Mayo Clin, Dept Neurol, Phoenix, AZ 85054 USA
[2] Arizona State Univ, Sch Comp, Informat, Decis Syst Engn, Phoenix, AZ USA
来源
HEADACHE | 2015年 / 55卷 / 06期
基金
美国国家科学基金会;
关键词
migraine; cortical thickness; cortical surface area; diagnostic classifier; magnetic resonance imaging; STATE FUNCTIONAL CONNECTIVITY; RESTING-STATE; NETWORK CONNECTIVITY; PAIN; ABNORMALITIES; SEGMENTATION; RESPONSES; ATTACKS; MODELS; CORTEX;
D O I
10.1111/head.12584
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background.-The International Classification of Headache Disorders provides criteria for the diagnosis and subclassification of migraine. Since there is no objective gold standard by which to test these diagnostic criteria, the criteria are based on the consensus opinion of content experts. Accurate migraine classifiers consisting of brain structural measures could serve as an objective gold standard by which to test and revise diagnostic criteria. The objectives of this study were to utilize magnetic resonance imaging measures of brain structure for constructing classifiers: (1) that accurately identify individuals as having chronic vs episodic migraine vs being a healthy control; and (2) that test the currently used threshold of 15 headache days/month for differentiating chronic migraine from episodic migraine. Methods.-Study participants underwent magnetic resonance imaging for determination of regional cortical thickness, cortical surface area, and volume. Principal components analysis combined structural measurements into principal components accounting for 85% of variability in brain structure. Models consisting of these principal components were developed to achieve the classification objectives. Tenfold cross validation assessed classification accuracy within each of the 10 runs, with data from 90% of participants randomly selected for classifier development and data from the remaining 10% of participants used to test classification performance. Headache frequency thresholds ranging from 5-15 headache days/month were evaluated to determine the threshold allowing for the most accurate subclassification of individuals into lower and higher frequency subgroups. Results.-Participants were 66 migraineurs and 54 healthy controls, 75.8% female, with an average age of 36 +/- 11 years. Average classifier accuracies were: (1) 68% for migraine (episodic + chronic) vs healthy controls; (2) 67.2% for episodic migraine vs healthy controls; (3) 86.3% for chronic migraine vs healthy controls; and (4) 84.2% for chronic migraine vs episodic migraine. The classifiers contained principal components consisting of several structural measures, commonly including the temporal pole, anterior cingulate cortex, superior temporal lobe, entorhinal cortex, medial orbital frontal gyrus, and pars triangularis. A threshold of 15 headache days/month allowed for the most accurate subclassification of migraineurs into lower frequency and higher frequency subgroups. Conclusions.-Classifiers consisting of cortical surface area, cortical thickness, and regional volumes were highly accurate for determining if individuals have chronic migraine. Furthermore, results provide objective support for the current use of 15 headache days/month as a threshold for dividing migraineurs into lower frequency (ie, episodic migraine) and higher frequency (ie, chronic migraine) subgroups.
引用
收藏
页码:762 / 777
页数:16
相关论文
共 50 条
  • [1] MAGNETIC-RESONANCE-IMAGING OF THE BRAIN IN PATIENTS WITH MIGRAINE
    IGARASHI, H
    SAKAI, F
    KAN, S
    OKADA, J
    TAZAKI, Y
    CEPHALALGIA, 1991, 11 (02) : 69 - 74
  • [2] Migraine classification using magnetic resonance imaging resting-state functional connectivity data
    Chong, Catherine D.
    Gaw, Nathan
    Fu, Yinlin
    Li, Jing
    Wu, Teresa
    Schwedt, Todd J.
    CEPHALALGIA, 2017, 37 (09) : 828 - 844
  • [3] Gray Matter Structural Alterations in Chronic and Episodic Migraine: A Morphometric Magnetic Resonance Imaging Study
    Planchuelo-Gomez, Alvaro
    Garcia-Azorin, David
    Guerrero, Angel L.
    Rodriguez, Margarita
    Aja-Fernandez, Santiago
    de Luis-Garcia, Rodrigo
    PAIN MEDICINE, 2020, 21 (11) : 2997 - 3011
  • [4] A volumetric magnetic resonance imaging study in migraine
    Naguib, Laila Elmously
    Azim, Ghada Saed Abdel
    Abdellatif, Mohammed Abdelrazek
    EGYPTIAN JOURNAL OF NEUROLOGY PSYCHIATRY AND NEUROSURGERY, 2021, 57 (01)
  • [5] Magnetic Resonance Imaging in Pediatric Migraine
    Webb, Megan E.
    Amoozegar, Farnaz
    Harris, Ashley D.
    CANADIAN JOURNAL OF NEUROLOGICAL SCIENCES, 2019, 46 (06) : 653 - 665
  • [6] Functional magnetic resonance imaging and brain functional connectivity in migraine
    Russo, Antonio
    Tedeschi, Gioacchino
    Tessitore, Alessandro
    JOURNAL OF HEADACHE AND PAIN, 2015, 16 : 1
  • [7] Dynamic functional connectivity of the migraine brain: a resting-state functional magnetic resonance imaging study
    Lee, Mi Ji
    Park, Bo-Yong
    Cho, Soohyun
    Park, Hyunjin
    Kim, Sung-Tae
    Chung, Chin-Sang
    PAIN, 2019, 160 (12) : 2776 - 2786
  • [8] Iron accumulation in deep brain nuclei in migraine: a population-based magnetic resonance imaging study
    Kruit, M. C.
    Launer, L. J.
    Overbosch, J.
    van Buchem, M. A.
    Ferrari, M. D.
    CEPHALALGIA, 2009, 29 (03) : 351 - 359
  • [9] Altered structural brain network topology in chronic migraine
    DeSouza, Danielle D.
    Woldeamanuel, Yohannes W.
    Sanjanwala, Bharati M.
    Bissell, Daniel A.
    Bishop, James H.
    Peretz, Addie
    Cowan, Robert P.
    BRAIN STRUCTURE & FUNCTION, 2020, 225 (01) : 161 - 172
  • [10] Functional magnetic resonance imaging and brain functional connectivity in migraine
    Antonio Russo
    Gioacchino Tedeschi
    Alessandro Tessitore
    The Journal of Headache and Pain, 2015, 16